Algorithm for Tracking of Fast Motion Objects with Adaptive Mean Shift

The classic kernel-based object tracking algorithm uses fixed kernel-bandwidth, which limits the performance when the object scale exceeds the size of the tracking window and the object fast motion. Therefor, a real-time object tracking algorithm is proposed, This algorithm gets the target's scale using automatic selection of kernel-bandwidth based on feature matching. Based on the analysis of similarity of object kernel-histogram by object center distance-weighting, gets the target's location by mean-shift algorithm. Experimental results show that the proposed algorithm can track successfully fast moving objects of changing in size.

[1]  Su Shu-guang.  Implement of Semi-fragile Blind Watermark Algorithm for H.264 Low Bit-Rates Video Stream , 2006 .

[2]  Martin Mauve,et al.  Local-lag and timewarp: providing consistency for replicated continuous applications , 2004, IEEE Transactions on Multimedia.

[3]  Dorin Comaniciu,et al.  Design, analysis, and engineering of video monitoring systems: an approach and a case study , 2001, Proc. IEEE.

[4]  Qibin Sun,et al.  A hybrid watermarking scheme for H.264/AVC video , 2004, ICPR 2004.

[5]  Ramani Duraiswami,et al.  Similarity Measure for Nonparametric Kernel Density Based Object Tracking , 2004 .

[6]  Ajay Luthra,et al.  Overview of the H.264/AVC video coding standard , 2003, IEEE Trans. Circuits Syst. Video Technol..

[7]  Larry D. Hostetler,et al.  The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.

[8]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[9]  Jing Zhang,et al.  Robust digital image-in-video watermarking for the emerging H.264/AVC standard , 2005, IEEE Workshop on Signal Processing Systems Design and Implementation, 2005..

[10]  Mingyu Lim,et al.  An Efficient Synchronization Mechanism Adapting to Dynamic Network State for Networked Virtual Environments , 2003, IS&T/SPIE Electronic Imaging.

[11]  Adnan M. Alattar,et al.  Digital watermarking of low bit-rate advanced simple profile MPEG-4 compressed video , 2003, IEEE Trans. Circuits Syst. Video Technol..

[12]  Christophe Diot,et al.  A distributed architecture for multiplayer interactive applications on the Internet , 1999, IEEE Netw..

[13]  David G. Lowe,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.

[14]  Yücel Altunbasak,et al.  An analysis of the DCT coefficient distribution with the H.264 video coder , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[15]  Eric Cronin,et al.  A Distributed Multiplayer Game Server System , 2001 .

[16]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Sugih Jamin,et al.  An Efficient Synchronization Mechanism for Mirrored Game Architectures , 2002, NetGames '02.

[18]  Edward J. Delp,et al.  Advances in Digital Video Content Protection , 2005, Proceedings of the IEEE.

[19]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Bernd Girod,et al.  Watermarking of uncompressed and compressed video , 1998, Signal Process..

[21]  Mubarak Shah,et al.  Target tracking in airborne forward looking infrared imagery , 2003, Image Vis. Comput..

[22]  Paul A. Viola,et al.  Alignment by Maximization of Mutual Information , 1997, International Journal of Computer Vision.

[23]  David R. Cheriton,et al.  Understanding the limitations of causally and totally ordered communication , 1994, SOSP '93.

[24]  Ramin Zabih,et al.  Bayesian multi-camera surveillance , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[25]  Alessio Del Bue,et al.  Smart cameras with real-time video object generation , 2002, Proceedings. International Conference on Image Processing.